Since most objects in COCO do not exhibit significant occlusions, we synthesize a large-scale instance segmentation dataset which contains 100k images following uniform class distribution for instances among the 80 categories in COCO. Each synthetic image has true and complete object contours for both occluding and partially occluded objects, thus allowing the explicit modeling of occlusion relationship between the occlusion regions and occluded objects. On the other hand, COCOA [1]}, which has only 5,000 images, relies on user annotation on a given training image for “guessing" occluded object boundaries. More details on our occlusion dataset synthesis process are provided in the supplementary file.
